The recent history and near future of digital health in the field of behavioral medicine: an update on progress from 2019 to 2024

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

The field of behavioral medicine has a long and successful history of leveraging digital health tools to promote health behavior change. Our 2019 summary of the history and future of digital health in behavioral medicine (Arigo in J Behav Med 8: 67–83, 2019) was one of the most highly cited articles in the Journal of Behavioral Medicine from 2010 to 2020; here, we provide an update on the opportunities and challenges we identified in 2019. We address the impact of the COVID-19 pandemic on behavioral medicine research and practice and highlight some of the digital health advances it prompted. We also describe emerging challenges and opportunities in the evolving ecosystem of digital health in the field of behavioral medicine, including the emergence of new evidence, research methods, and tools to promote health and health behaviors. Specifically, we offer updates on advanced research methods, the science of digital engagement, dissemination and implementation science, and artificial intelligence technologies, including examples of uses in healthcare and behavioral medicine. We also provide recommendations for next steps in these areas with attention to ethics, training, and accessibility considerations. The field of behavioral medicine has made meaningful advances since 2019 and continues to evolve with impressive pace and innovation.

Related collections

Most cited references 120

Record: found
Abstract: not found
Article: not found

Large language models in medicine

Arun James Thirunavukarasu, Darren Shu Jeng Ting, Kabilan Elangovan … (2023)

0 comments Cited 434 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Conceptualising engagement with digital behaviour change interventions: a systematic review using principles from critical interpretive synthesis

Olga Perski, Ann Blandford, Robert L. West … (2016)

“Engagement” with digital behaviour change interventions (DBCIs) is considered important for their effectiveness. Evaluating engagement is therefore a priority; however, a shared understanding of how to usefully conceptualise engagement is lacking. This review aimed to synthesise literature on engagement to identify key conceptualisations and to develop an integrative conceptual framework involving potential direct and indirect influences on engagement and relationships between engagement and intervention effectiveness. Four electronic databases (Ovid MEDLINE, PsycINFO, ISI Web of Knowledge, ScienceDirect) were searched in November 2015. We identified 117 articles that met the inclusion criteria: studies employing experimental or non-experimental designs with adult participants explicitly or implicitly referring to engagement with DBCIs, digital games or technology. Data were synthesised using principles from critical interpretive synthesis. Engagement with DBCIs is conceptualised in terms of both experiential and behavioural aspects. A conceptual framework is proposed in which engagement with a DBCI is influenced by the DBCI itself (content and delivery), the context (the setting in which the DBCI is used and the population using it) and the behaviour that the DBCI is targeting. The context and “mechanisms of action” may moderate the influence of the DBCI on engagement. Engagement, in turn, moderates the influence of the DBCI on those mechanisms of action. In the research literature, engagement with DBCIs has been conceptualised in terms of both experience and behaviour and sits within a complex system involving the DBCI, the context of use, the mechanisms of action of the DBCI and the target behaviour. Electronic supplementary material The online version of this article (doi:10.1007/s13142-016-0453-1) contains supplementary material, which is available to authorized users.

0 comments Cited 378 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Conversational agents in healthcare: a systematic review

Liliana Laranjo, Adam G Dunn, Huong Ly Tong … (2018)

Abstract Objective Our objective was to review the characteristics, current applications, and evaluation measures of conversational agents with unconstrained natural language input capabilities used for health-related purposes. Methods We searched PubMed, Embase, CINAHL, PsycInfo, and ACM Digital using a predefined search strategy. Studies were included if they focused on consumers or healthcare professionals; involved a conversational agent using any unconstrained natural language input; and reported evaluation measures resulting from user interaction with the system. Studies were screened by independent reviewers and Cohen’s kappa measured inter-coder agreement. Results The database search retrieved 1513 citations; 17 articles (14 different conversational agents) met the inclusion criteria. Dialogue management strategies were mostly finite-state and frame-based (6 and 7 conversational agents, respectively); agent-based strategies were present in one type of system. Two studies were randomized controlled trials (RCTs), 1 was cross-sectional, and the remaining were quasi-experimental. Half of the conversational agents supported consumers with health tasks such as self-care. The only RCT evaluating the efficacy of a conversational agent found a significant effect in reducing depression symptoms (effect size d = 0.44, p = .04). Patient safety was rarely evaluated in the included studies. Conclusions The use of conversational agents with unconstrained natural language input capabilities for health-related purposes is an emerging field of research, where the few published studies were mainly quasi-experimental, and rarely evaluated efficacy or safety. Future studies would benefit from more robust experimental designs and standardized reporting. Protocol Registration The protocol for this systematic review is registered at PROSPERO with the number CRD42017065917.

0 comments Cited 259 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Danielle Arigo:

ORCID: http://orcid.org/0000-0002-7807-5913

arigo@rowan.edu

Journal

Journal ID (nlm-ta): J Behav Med

Journal ID (iso-abbrev): J Behav Med

Title: Journal of Behavioral Medicine

Publisher: Springer US (New York )

ISSN (Print): 0160-7715

ISSN (Electronic): 1573-3521

Publication date (Electronic): 28 October 2024

Publication date PMC-release: 28 October 2024

Publication date (Print): 2025

Volume: 48

Issue: 1

Pages: 120-136

Affiliations

[1 ]Department of Psychology, Rowan University, ( https://ror.org/049v69k10) Glassboro, NJ USA

[2 ]Department of Family Medicine, Rowan-Virtua School of Osteopathic Medicine, ( https://ror.org/049v69k10) Stratford, NJ USA

[3 ]Department of Biomedical Sciences, Cooper Medical School of Rowan University, ( https://ror.org/007evha27) Camden, NJ USA

[4 ]Department of Health Education & Behavior, University of Florida, ( https://ror.org/02y3ad647) Gainesville, FL USA

[5 ]Department of Allied Health Sciences, Center for mHealth and Social Media, Institute for Collaboration in Health, Interventions, and Policy, University of Connecticut, ( https://ror.org/02der9h97) Storrs, CT USA

Author information

Danielle Arigo http://orcid.org/0000-0002-7807-5913

Article

Publisher ID: 526

DOI: 10.1007/s10865-024-00526-x

PMC ID: 11893649

PubMed ID: 39467924

SO-VID: 87067dea-ce0d-42f4-929d-49160f233305

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 30 August 2024

Date accepted : 6 October 2024

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100000050, National Heart, Lung, and Blood Institute;

Award ID: K23HL36657

Award ID: DP2HL73857

Award ID: K24HL124366

Award Recipient : Danielle Arigo Sherry L. Pagoto

Funded by: Rowan University

Open Access :

Open access funding provided by Rowan University

Custom metadata

ScienceOpen disciplines: Neurology

Keywords: digital health,mobile applications,behavior change intervention,artificial intelligence,wearable technology

Data availability:

ScienceOpen disciplines: Neurology

Keywords: digital health, mobile applications, behavior change intervention, artificial intelligence, wearable technology

Comments

Comment on this article

scite_

Smart Citations

Citing PublicationsSupportingMentioningContrasting

View Citations

See how this article has been cited at scite.ai

scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

Most referenced authors 1,001

See all reference authors

The recent history and near future of digital health in the field of behavioral medicine: an update on progress from 2019 to 2024

Read this article at

Abstract

Related collections

Novel Coronavirus Disease COVID-19

Most cited references 120

Large language models in medicine

Conceptualising engagement with digital behaviour change interventions: a systematic review using principles from critical interpretive synthesis

Conversational agents in healthcare: a systematic review

Author and article information

Contributors

Journal

Affiliations

Author information

Article

History

Funding

Categories

Custom metadata

Comments

Comment on this article

Similar content 78

Most referenced authors 1,001